Molecular design of organic photovoltaic donors and non-fullerene acceptors: a combined machine learning and genetic algorithm approach
Rui Cao, Cai‐Rong Zhang, Xiaomeng Liu, Ji-Jun Gong, Meiling Zhang, Zi‐Jiang Liu, Youzhi Wu, Hong-Shan Chen
Abstract
A 480-pair donor–acceptor database with 43 descriptors predicted photovoltaic parameters via random forest. Novel pairs via genetic algorithm achieved 16.85% efficiency, offering an efficient method for organic solar cells and molecular design.
Topics & Concepts
FullerenePhotovoltaic systemMaterials scienceGenetic algorithmOrganic solar cellAlgorithmArtificial intelligenceNanotechnologyMachine learningComputer scienceOrganic chemistryElectrical engineeringEngineeringChemistryOrganic Electronics and PhotovoltaicsConducting polymers and applicationsMachine Learning in Materials Science